Collecting High-Quality Data – Quiz 2

Quiz Question Explanations

Question 1

Systematic error means the data are typically incorrect, but in the same direction (e.g. inflated), which will lead to the mean being inflated, which is an example of bias. Random error leads to more noise (not hitting the target right on, sometimes inflated, sometimes deflated), but as long as we’re taking the average over a large enough sample, those errors should cancel each other out on average. But the variance may be larger than otherwise, which is our definition of imprecise.

Question 2

False! If observations are consistently inflated, the estimated mean (or regression coefficient) of those results will also likely be inflated, no matter how many observations we include to calculate our estimate.

Question 3

True! While sample size cannot get rid of systematic error, it can increase precision whether side variance is caused by a very wide distribution of true outcomes, or noise due to random error.